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Training memory-constrained deep learning models using automatic dataflow-graph partitioning

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dc.contributor.advisorErten, Didem Unat
dc.contributor.advisorid0000-0002-2351-0770
dc.contributor.authorQararyah, Fareed Mohammad Fareed
dc.contributor.instituteKoç University Graduate School of Sciences and Engineering
dc.contributor.programComputer Engineering
dc.contributor.yokid219274
dc.date.accessioned2024-11-09T22:06:46Z
dc.date.issued2020
dc.descriptionxv, 59 leaves : tables, graphics ; 30 cm.
dc.identifier.urihttps://hdl.handle.net/20.500.14288/4877
dc.languageEnglish
dc.publisherKoç University
dc.relation.collectionKU Theses and Dissertations
dc.rightsrestrictedAccess
dc.rights.copyrightsnote© All Rights Reserved. Accessible to Koç University Affiliated Users Only!
dc.subjectNeural networks (Computer science)
dc.subjectDeep learning
dc.subjectComputational learning theory
dc.subjectMachine learning
dc.subjectArtificial intelligence
dc.thesis.degreeMaster's Degree
dc.thesis.grantorİstanbul
dc.titleTraining memory-constrained deep learning models using automatic dataflow-graph partitioning
dc.typeThesis
dspace.entity.typePublication
relation.isAdvisorOfThesisf8fda873-fa1c-4b24-9645-38a5a1c40353
relation.isAdvisorOfThesis.latestForDiscoveryf8fda873-fa1c-4b24-9645-38a5a1c40353

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